1. Field of the Invention
The present invention relates to an abnormality detection apparatus and method for detecting an event where, for example, a person has fallen in a room such as a bathroom, toilet or the like.
2. Prior Art
Recent years have seen an increasing number of bathroom accidents involving the deaths of persons taking bath. The number of people who died during bath use exceeds that of those who were killed in traffic accidents. Accordingly, attention is being focused on the accidents during bath use.
The direct causes of the accidental deaths during bath use are that a bath user fell because of heart failure or cerebral apoplexy and that a bath user, having lost consciousness, was drowned to death in a bath-tub. Although study has been made to investigate the causative factor of such situations, it is rather difficult to identify the causative factor under the current circumstances with changes in life styles further complicating the problem. Accordingly, it is quite difficult to prevent the occurrence of heart failure or cerebral apoplexy during bath use.
However, the chance of surviving such situations can be significantly increased by early detection although the episodes of the diseases cannot be prevented.
In this connection, Japanese Unexamined Patent Publication No.11(1999)-101502 has disclosed an abnormality detection system which operates as follows. The system monitors a bathroom to capture such a coarse image for privacy protection that only the presence of a bath user can barely be recognized, for calculation of a position of the centroid of the bath user. The system detects a motion of the bath user by sensing the movement of the centroid in order to inform a kitchen of an abnormality if the motion cannot be detected for a predetermined period of time.
In the room, however, there are usually other moving objects than the person. The other moving objects in the bathroom may be exemplified by shower water, wavering surface of hot water in the bath-tub and the like. In the prior-art system adapted to detect the motion of a person based on the coarse image, it is difficult to differentiate the motion of the person from the shower water or the wavering surface of hot water in the tub. This sometimes leads to a case where despite the cease of motion of the bath user, the system cannot detect the abnormal state of the user because it has mistaken the shower water or the wavering water surface for the motion of the user.
It is an object of the invention to provide an abnormality detection apparatus and method for high accuracy detection of an event where a person has fallen in a room such as a bathroom, toilet or the like.
In accordance with the invention, an abnormality detection apparatus for detecting an event where a monitored object in a room has lapsed into an abnormal state, the apparatus comprises image pickup means for picking up an image of a scene in the room; feature-quantity extraction means for extracting an image feature-quantity from the image picked up by the image pickup means; and judgment means for determining whether the monitored object in the room has lapsed into the abnormal state or not based on the time-variations of the image feature quantity extracted by the feature-quantity extraction means.
A usable feature-quantity extraction means is adapted to, for example, calculate the image feature quantity of each of plural feature-quantity calculation regions defined in one screen, the calculation performed on the feature-quantity calculation regions at predetermined time intervals. A usable judgment means is adapted to, for example, determine whether the monitored object in the room has lapsed into the abnormal state or not based on the time-variations of the respective image feature quantities of the feature-quantity calculation regions.
The usable judgment means comprises, for example, means for judging the respective feature-quantity calculation regions as to whether the image feature quantity is time-varied or not, the judgment made on the calculation regions at predetermined time intervals; means for determining whether the feature-quantity calculation regions determined to be time-varied in the image feature quantities are present in not less than a predetermined number or less than the predetermined number each time the judgment as to the time-variations of the image feature quantities is made; and means for determining that the monitored object has lapsed into the abnormal state when a state with less than the predetermined number of feature-quantity calculation regions determined to be time-varied in the image feature quantities has continued for a predetermined period of time.
In a case where a first alarm device is installed in the room while a second alarm device is installed outside the room, a usable judgment means comprises, for example, means for judging the respective feature-quantity calculation regions as to whether the image feature quantity is time-varied or not, the judgment made on the calculation regions at predetermined time intervals; means for determining whether the feature-quantity calculation regions determined to be time-varied in the image feature quantities are present in not less than a predetermined number or less than the predetermined number each time the judgment as to the time-variations of the image feature quantities is made; means for triggering the first alarm device when a state with less than the predetermined number of feature-quantity calculation regions determined to be time-varied in the image feature quantities has continued for a first predetermined period of time; and means for triggering the second alarm device when the state with less than the predetermined number of feature-quantity calculation regions determined to be time-varied in the image feature quantities has continued for a second predetermined period of time which is longer than the first predetermined period of time.
A usable judgment means comprises, for example, first judging means for judging the respective feature-quantity calculation regions as to whether the image feature quantity is time-varied or not, the judgment made on the calculation regions at predetermined time intervals; second judging means for determining whether feature-quantity calculation regions determined to be time-varied in the image feature quantities are present in not less than a predetermined number or less than the predetermined number each time the judgment as to the time-variations of the image feature quantities is made; and third judging means for determining whether the monitored object has lapsed into the abnormal state or not based on a predetermined number of preceding judgment results given by the second judging means.
In a case where the first alarm device is installed in the room while the second alarm device is installed outside the room, a usable judgment means comprises, for example, first judging means for judging the respective feature-quantity calculation regions as to whether the image feature quantity is time-varied or not, the judgment made on the calculation regions at predetermined time intervals; second judging means for determining whether the monitored object is in motion or not each time the judgment as to the time-variations of the image feature quantities is made, the judgment made based on whether the feature-quantity calculation regions determined to be time-varied in the image feature quantities are present in not less than a predetermined number or less than the predetermined number; means for triggering the first alarm device when a first predetermined number of preceding judgment results given by the second judging means include not more than a first predetermined number of determinations that the monitored object is in motion; and means for triggering the second alarm device when a second predetermined number of preceding judgment results given by the second judging means include not more than a second predetermined number of determinations that the monitored object is in motion.
A usable feature-quantity extraction means is adapted to, for example, calculate an average of image feature quantities for a predetermined number of fields with respect to each of plural feature-quantity calculation regions defined in one screen, the calculation performed on the calculation regions at predetermined time intervals. A usable judgment means is adapted to, for example, determine whether the monitored object in the room has lapsed into the abnormal state or not based on the time-variations of the respective average image feature quantities of the feature-quantity calculation regions.
A usable judgment means comprises, for example, means for judging the respective feature-quantity calculation regions as to whether the average image feature quantity is time-varied or not, the judgment made on the calculation regions at predetermined time intervals; means for determining whether the feature-quantity calculation regions determined to be time-varied in the average image feature quantities are present in not less than a predetermined number or less than the predetermined number each time the judgment as to the time-variations of the average image feature quantities is made; and means for determining that the monitored object has lapsed into the abnormal state when a state with less than the predetermined number of feature-quantity calculation regions determined to be time-varied in the average image feature quantities has continued for a predetermined period of time.
In a case where the first alarm device is installed in the room while the second alarm device is installed outside the room, a usable judgment means comprises, for example, means for judging the respective feature-quantity calculation regions as to whether the average image feature quantity is time-varied or not, the judgment made on the calculation regions at predetermined time intervals; means for determining whether the feature-quantity calculation regions determined to be time-varied in the average image feature quantities are present in not less than a predetermined number or less than the predetermined number each time the judgment as to the time-variations of the average image feature quantities is made; means for triggering the first alarm device when a state with less than the predetermined number of feature-quantity calculation regions determined to be time-varied in the average image feature quantities has continued for a first predetermined period of time; and means for triggering the second alarm device when the state with less than the predetermined number of feature-quantity calculation regions determined to be time-varied in the average image feature quantities has continued for a second predetermined period of time which is longer than the first predetermined period of time.
In accordance with the invention, an abnormality detection method for detecting an event where a monitored object in a room has lapsed into an abnormal state, the method comprises the steps of: a first step of picking up an image of a scene in the room via an image pickup device; a second step of extracting an image feature quantity from the image captured at the first step; and a third step of determining whether the monitored object has lapsed into the abnormal state or not based on the time-variations of the image feature quantity extracted at the second step.
The second step is adapted to, for example, calculate an image feature quantity of each of plural feature-quantity calculation regions defined in one screen, the calculation performed on the calculation regions at predetermined time intervals. The third step is adapted to, for example, determine whether the monitored object in the room has lapsed into the abnormal state or not based on the time-variations of the respective image feature quantities of the feature-quantity calculation regions.
For example, the third step comprises the steps of: judging the respective feature-quantity calculation regions as to whether the image feature quantity is time-varied or not, the judgment made on the calculation regions at predetermined time intervals; determining whether the feature-quantity calculation regions determined to be time-varied in the image feature quantities are present in not less than a predetermined number or less than the predetermined number each time the judgment as to the time-variations of the image feature quantities is made; and determining that the monitored object has lapsed into the abnormal state when a state with less than the predetermined number of feature-quantity calculation regions determined to be time-varied in the image feature quantities has continued for a predetermined period of time.
In a case where the first alarm device is installed in the room while the second alarm device is installed outside the room, the third step comprises, for example, the steps of: judging the respective feature-quantity calculation regions as to whether the image feature-quantity is time-varied or not, the judgment made on the calculation regions at predetermined time intervals; determining whether the feature-quantity calculation regions determined to be time-varied in the image feature quantities are present in not less than a predetermined number or less than the predetermined number each time the judgment as to the time-variations of the image feature quantities is made; triggering the first alarm device when a state with less than the predetermined number of feature-quantity calculation regions determined to be time-varied in the image feature quantities has continued for a first predetermined period of time; and triggering the second alarm device when the state with less than the predetermined number of feature-quantity calculation regions determined to be time-varied in the image feature quantities has continued for a second predetermined period of time which is longer than the first predetermined period of time.
For example, the third step comprises: Step xe2x80x98axe2x80x99 of judging the respective feature-quantity calculation regions as to whether the image feature quantity is time-varied or not, the judgment made on the calculation regions at predetermined time intervals; Step xe2x80x98bxe2x80x99 of determining whether the feature-quantity calculation regions determined to be time-varied in the image feature quantities are present in not less than a predetermined number or less than the predetermined number each time the judgment as to the time-variations of the image feature quantities is made; and Step xe2x80x98cxe2x80x99 of determining whether the monitored object has lapsed into the abnormal state or not based on a predetermined number of preceding judgment results given by Step xe2x80x98bxe2x80x99.
In a case where the first alarm device is installed in the room while the second alarm device is installed outside the room, the third step comprises, for example, Step xe2x80x98axe2x80x99 of judging the respective feature-quantity calculation regions as to whether the image feature quantity is time-varied or not, the judgment made on the calculation regions at predetermined time intervals; Step xe2x80x98bxe2x80x99 of determining whether the feature-quantity calculation regions determined to be time-varied in the image feature quantities are present in not less than a predetermined number or less than the predetermined number each time the judgment as to the time-variations of the image feature quantities is made, thereby determining whether the monitored object has lapsed into the abnormal state or not; Step xe2x80x98cxe2x80x99 of triggering the first alarm device when a first predetermined number of preceding judgment results given by Step xe2x80x98bxe2x80x99 include not more than a first predetermined number of determinations that the monitored object is in motion; and Step xe2x80x98dxe2x80x99 of triggering the second alarm device when a second predetermined number of preceding judgment results given by Step xe2x80x98bxe2x80x99 include not more than a second predetermined number of determinations that the monitored object is in motion.
The second step is adapted to, for example, calculate an average of image feature quantities for a predetermined number of fields with respect to each of plural feature-quantity calculation regions defined in one screen, the calculation performed on the calculation regions at predetermined time intervals. The third step is adapted to, for example, determine whether the monitored object in the room has lapsed into the abnormal state or not based on the time-variations of the respective average image feature quantities of the feature-quantity calculation regions.
For example, the third step comprises the steps of: judging the respective feature-quantity calculation regions as to whether the average image feature quantity is time-varied or not, the judgment made on the calculation regions at predetermined time intervals; determining whether the feature-quantity calculation regions determined to be time-varied in the average image feature quantities are present in not less than a predetermined number or less than the predetermined number each time the judgment as to the time-variations of the average image feature quantities is made; and determining that the monitored object has lapsed into the abnormal state when a state with less than the predetermined number of feature-quantity calculation regions determined to be time-varied in the average image feature quantities has continued for a predetermined period of time.
In a case where the first alarm device is installed in the room while the second alarm device is installed outside the room, the third step comprises, for example, the steps of: judging the respective feature-quantity calculation regions as to whether the average image feature quantity is time-varied or not, the judgment made on the calculation regions at predetermined time intervals; determining whether the feature-quantity calculation regions determined to be time-varied in the average image feature quantities are present in not less than a predetermined number or less than the predetermined number each time the judgment as to the time-variations of the average image feature quantities is made; triggering the first alarm device when a state with less than the predetermined number of feature-quantity calculation regions determined to be time-varied in the average image feature quantities has continued for a first predetermined period of time; and triggering the second alarm device when the state with less than the predetermined number of feature-quantity calculation regions determined to be time-varied in the average image feature quantities has continued for a second predetermined period of time which is longer than the first predetermined period of time.